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We present a novel motion descriptor for gesture recognition based on depth camera. Since each object motion leads to a specific depth change characterized by depth difference, we can recognize object motion via Depth Difference Distribution (DDD) in object region. The DDD is approximated by DDD descriptor in three steps. First, each pixel's depth difference value is quantified into Depth Difference...
Reading text from scene images is a challenging problem that is receiving much attention, especially since the appearance of imaging devices in low-cost consumer products like mobile phones. This paper presents an easy and fast method to recognize individual characters in images of natural scenes that is applied after an algorithm that robustly locates text on such images. The recognition is based...
We extend the PCT (Pseudo Census Transform)-based appearance model [3] to ranking-based appearance model for face alignment. The PCT-based weak ranking function is learned using RankSVM, and the ranking appearance model (RAM) is constructed in a boosting manner. Experiments show that the PCT-based RAM is more robust and generalize better than the PCT-based boosted appearance model (BAM). The PCT-RAM...
We have been manufacturing our own License Plate Recognition (LPR) systems since 1999 for parking lots in Japan. We have implemented a number of enhancements for our latest LPR system and one of the most important enhancements is for ranges of acceptable license-plate attitude angles. We collected 163, 574 actual images so far and we selected 6,648 images randomly from this image database to verify...
This paper addresses the problem of shape classification and proposes a method able to exploit peculiarities of both, local and global shape descriptors. In the proposed shape classification framework, the silhouettes of symbols are firstly described through Bags of Shape Contexts. This shape signature is used to solve correspondence problem between points of two shapes. The obtained correspondences...
In this paper we develop a practical method for estimating shape and reflectance using only three polarised images. Using polarised light and retro-reflection settings during image acquisition, we separate the diffuse and specular reflectance components using Blind Source Separation without the accurate knowledge of the polariser angle information. Next, we compare the capacities of five chosen reflectance...
3D-model processing plays an important role in numerous applications. In this paper, we present an approach for 3D-model retrieval by creating index of closed curves in R3 generated from the center of a 3D-model, using a commute time mapping function. Our mapping function respects important properties in order to compute robust closed curves. Each curve describes a small region of the 3D-model. To...
This paper proposes a robust detection method for circular objects in noisy and inhomogeneous contrast image. This method detects circular objects not by the difference in image intensities between the object interior and its surrounding, but by the separability and uniformity of the image intensity distributions as calculated by Bhattacharyya Coefficient. The proposed method can detect obscure and...
We present a method for recovering fast and robustly the 3D shape of inextensible and smooth surfaces from a monocular image. We propose a weighted iterative least squares approach to minimize the reprojection error between 2D-3D point correspondences preserving the 3D lengths. In addition, a local 3D smoothness constraint for each mesh vertex is proposed to increase the robustness to noisy correspondences...
It is suggested how a Markov random field can be used for object tracking with context information. The tracking is formulated as a two layer process. In the first phase, the image is represented by a set of feature points which are tracked by a standard tracker. In the second phase, the proposed semi-supervised learning and labeling algorithm is used to label the points to three classes — object,...
Finding correspondences between two 3D shapes is common both in computer vision and computer graphics. In this paper, we propose a general framework that shows how to build correspondences by utilizing the isometric property. We show that the problem of finding such correspondences can be reduced to the problem of spectral assignment, which can be solved by finding the principal eigenvector of the...
Many problems in computer vision and robotics rely on automatically determining point correspondences from two images. Due to issues such as illumination variations, uncontrolled acquisition conditions and noise, this is a challenging problem. This work presents a method that combines visual and shape information to perform point correspondences which is invariant to rotation and scaling transformations...
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